Integrating transcriptomics, glycomics and glycoproteomics to characterize hepatitis B virus-associated hepatocellular carcinoma

Background Hepatocellular carcinoma (HCC) ranks as the third most common cause of cancer related death globally, representing a substantial challenge to global healthcare systems. In China, the primary risk factor for HCC is the hepatitis B virus (HBV). Aberrant serum glycoconjugate levels have long been linked to the progression of HBV-associated HCC (HBV-HCC). Nevertheless, few study systematically explored the dysregulation of glycoconjugates in the progression of HBV-associated HCC and their potency as the diagnostic and prognostic biomarker. Methods An integrated strategy that combined transcriptomics, glycomics, and glycoproteomics was employed to comprehensively investigate the dynamic alterations in glyco-genes, N-glycans, and glycoproteins in the progression of HBV- HCC. Results Bioinformatic analysis of Gene Expression Omnibus (GEO) datasets uncovered dysregulation of fucosyltransferases (FUTs) in liver tissues from HCC patients compared to adjacent tissues. Glycomic analysis indicated an elevated level of fucosylated N-glycans, especially a progressive increase in fucosylation levels on IgA1 and IgG2 determined by glycoproteomic analysis. Conclusions The findings indicate that the abnormal fucosylation plays a pivotal role in the progression of HBV-HCC. Systematic and integrative multi-omic analysis is anticipated to facilitate the discovery of aberrant glycoconjugates in tumor progression. Supplementary Information The online version contains supplementary material available at 10.1186/s12964-024-01569-y.


Introduction
Hepatocellular carcinoma (HCC) is a primary liver malignancy and ranks as the third leading cause of cancer-related death worldwide [1].Hepatitis B and C viral infections are the two major etiologies of HCC [2,3], with chronic HBV being predominating in China due to the high prevalence of HBV infection [4,5].The relative risk of HCC in HBV-positive patients compared to HBVnegative controls is much higher [6].Most HBV-HCC patients experience a trilogy of hepatitis-cirrhosis-HCC [7,8].Alpha-fetoprotein (AFP) is the most commonly used serum biomarker for HCC since it was discovered in 1964 [9].However, approximately 30% of patients with early-stage HCC are AFP negative [10], and elevated AFP levels are also detected in patients with cirrhosis or chronic HCV exacerbations [11].Indeed, most cancer markers used in clinics are glycoproteins [12], and their glycan moieties may be structurally different in cancer [13].Therefore, a global analysis of the precise variation of glycoconjugates in HBV-HCC is urgently needed.
As one of the terminal modifications, fucosylation is the process of transferring fucose from GDP-fucose to their substrates by fucosyltransferases in all mammalian cells [26].Recent studies revealed that levels of core and outer-armer fucosylation were increased in the serum of patients with HCC [27].The cancer-promoting capacity of cancer-associated fibroblasts was facilitated by modifying EGFR core fucosylation in non-small cell lung cancer [28].Some highly abundant serum proteins such as transferrin (TF) and alpha-1-anti-trypsin (A1AT) were found to be decorated with increased levels of fucosylation in HCC [29].These results demonstrate that glycosylation shows the potential as an indicator of liver disease progression to HCC.However, these studies commonly focus on cancer and adjacent tissues, rather than the process of liver disease from healthy control to HCC.In addition, each omics approach, such as transcriptomics, glycomics and glycoproteomics, cannot capture the entire biological complexity of most human diseases.
Therefore, an integration of multiple omics approaches can provide a more comprehensive information on biological significance and diagnostic potential of glycans in the process of HCC.
In this study, multi-omics including transcriptomics, glycomics, and glycoproteomics were integrated to profile the aberrant levels of glycan-related gene, glycan pattern, site-specific glycoproteins in HBV-HCC process.

Patients and samples
Three pairs of HBV-HCC and adjacent tissues, and serum samples from 27 chronic hepatitis B (CHB), 22 HBVrelated liver cirrhosis (LC), 31 HBV-HCC patients and 20 healthy controls (HC) were collected from The First Affiliated Hospital of Xi'an Medical University.Informed consent was conducted in accordance with Declaration of Helsinki and experiments were approved by The First Affiliated Hospital of Xi'an Medical University Ethics Committee.Characteristic of samples are listed in Table S1&2.

GEO data analysis
The gene expression profile data GSE135631 and GSE94660 was downloaded from GEO of the National Center for Biotechnology Information (NCBI).Gene expression data deposited as the Series Matrix data was used for analysis of the fold change of gene expression and p value.

Quantitative reverse transcription PCR (RT-qPCR)
RNA from the indicated tissues was extracted using Trizol (ABclonal; Wuhan, Hubei, China) and reversed transcribed using the cDNA Reverse Transcription Kit (ABclonal).RT-qPCR was performed using SYBR Green Master Mix using Real-Time PCR system (TIANLONG; Xi'an, Shaanxi, China).Primer sequences were provided in Table S3.
Lyophilized N-glycans were dissolved and spotted onto an MTP AnchorChip sample target with 20 mg/ mL 2,5-dihydroxybenzoic acid (DHB) as the matrix.Measurements were taken in positive-ion mode.Each full-mass scan was performed with following conditions: acceleration voltage, 24.59 kV; reflector voltage, 26.6 kV; pulsed ion extraction, 100 ns; mass range, 1000-3500 m/z.For the data analysis, the peaks were smoothed and baseline subtraction performed three times.Relative intensity was analyzed and generated using FlexAnalysis software (Bruker Daltonics; Bremen, Germany) based on MALDI-TOF/TOF-MS intensity.m/z data were obtained and annotated using GlycoWorkbench software program [31], cross-referenced with previous studies [32][33][34], together with knowledge of mammalian glycan biosynthetic pathway products.For the isomeric structures that are not easily deciphered by MALDI-TOF-MS, uncertainties in sequences, especially fuzzily defined capping unit locations, have been indicated outside the bracket in the proposed N-glycan structure.

Proteomics and glycoproteomics
Protein extraction and digestion was performed as previously described [30].In brief, the serum protein was denatured in 8 M urea/ 50 mM NH 4 HCO 3 , then reduced with DTT, alkylated with IAM, digested with lysyl endopeptidase (Promega; Madison, WI, USA) for 4 h at 37 °C, and then incubated with trypsin (Promega) overnight at 37 °C with shaking.The digested peptides were acidified with 10% trifluoroacetic acid to pH < 3, collected by centrifugation and purified using Oasis HLB cartridges (Waters; Milford, MA, USA).Desalted peptides were subjected to LC-MS/MS analysis for proteomics.N-glycopeptides were enriched by MAX column (Waters) using desalted peptides, and subjected to LC-MS/MS analysis for glycoproteomics as described previously [35].

Enzyme-Linked Immunosorbent Assay (ELISA)
To determine the Igs levels in serum, direct ELISA was applied.ELISA plates were coated with serum sample for 2 h at 37 °C, blocked with 3% BSA in PBS for 2 h at room temperature (RT), rinsed with PBST, incubated with antibody against IgA1 or IgG2 (Abcam; Cambridge, MA, USA) for 2 h at 37 °C, rinsed with PBST, incubated with secondary antibody for 30 min at RT, rinsed with PBST, and visualized with TMB substrate kit (Beyotime Institute of Biotechonology; Haimen, China).The absorbance values were determined at 450 nm with a plate reader.
To determine the glycosylation on Igs, sandwich ELISA was performed.ELISA plates were coated with antibodies against IgA1 or IgG2 overnight at 4 °C, rinsed with PBST, blocked with 5% BSA, incubated with serum samples for 2 h at 37 °C, rinsed with PBST, incubated with biotinylated lectins (Vector Labs) overnight at 4 °C, incubated with VECTASTAIN ABC reagent for 30 min at RT, and visualized with TMB substrate solution.The absorbance values were determined at 450 nm with a plate reader.

Data analysis
All experiments were reproduced at least three times.All values were presented as mean ± standard deviation (SD).Two-tailed Student's t-test was used for comparison of data sets between two groups and differences with p < 0.05 were considered statistically significant.Statistical analysis was performed using GraphPad Prism 9.3.1 software program.

Glycan-related genes expression of HBV-HCC and adjacent tissues
A better understanding of glyco-gene expression changes may facilitate the exploration of association between glycosylation and HBV-HCC.The differences in glycogene expression and glycosylation in HBV-HCC were investigated using an integrated strategy with a combination of transcriptomics, glycomics and glycoproteomics (Fig. 1A).First, GSE135631 and GSE94660 gene expression profiles, including 15 and 21 pairs of HBV-HCC and adjacent tissues respectively, were retrieved from the GEO database.A total of 7502 and 7839 genes were differentially expressed in GSE135631 and GSE94660, as shown in Fig. 1B, in which top 100 differentially expressed glyco-genes (DEGGs) were highlighted (Fig. 1B, Table S4).Partial Least Squares Discrimination Analysis (PLS-DA) of these DEGGs exhibited a clear separation of HBV-HCC from adjacent tissues (Fig. 1C).The expression patterns of all DEGGs across HBV-HCC and adjacent tissues from the combined two GSE study (See figure on next page.)Fig. 1 Differentially expressed glycan-related genes in HBV-related HCC of GSE135631 and GSE94660.A Workflow of the present study.B Volcano plot of expression patterns of identified genes in GSE135631 and GSE94660.Red dots: up-regulated genes.Green dots: down-regulated genes.Highlighted dots: DEGGs.The q value (log10) is plotted against the log10 (FC: HBV-HCC tissues vs. adjacent tissues) using the cut-offs of fold change > 1.5 or < 0.67 and p value < 0.05.C PLS-DA plot of DEGGs in GSE135631 and GSE94660.D Heatmap showing the expression pattern of DEGGs in HBV-HCC and adjacent tissues of GSE135631 and GSE94660.E Functional enrichment analysis of DEGGs.F The PPI network of DEGGs performed by the STRING database and cytoscape tools.The red colour intensity was proportional to the degree of connectivity.G The mRNA expression of 13 FUTs, PIGV, PIGT, PIGM and B4GALT3 genes in 3 pairs of HBV-HCC and adjacent tissues determined by RT-qPCR were shown as a heatmap (Fig. 1D).Next, functional enrichment analysis revealed that the main molecular function categories were carbohydrate binding, transferring glycosyl and hexosyl group activity (Fig. 1E).Protein-protein interaction (PPI) network of these DEGGs was constructed in an attempt to explicit the molecular mechanisms in the progression of HBV-HCC.Clustering analysis revealed ten major modules, in which protein glycosylation, GPI anchor biosynthetic process and glycosylation processes were mostly enriched (Fig. 1F; S1).Hub genes with a high degree of connectivity in the PPI network are significantly enriched in the process of fucosylation (FUT4, FUT6, FUT2 and FUT1), GPI anchor biosynthesis (PIGM, PIGV, PIGT and GPAA1), galactosylation (B4GALT3) and galNAcylation (B3GNT3).
Furthermore, FUTs family expression at mRNA levels were determined by RT-qPCR in HBV-HCC and adjacent tissues (Fig. 1G), revealed an elevated level of FUT1, FUT2, FUT4, FUT5, FUT8, FUT10, PIGT, PIGM and B4GALT3, as well as a reduced level of FUT3, FUT6, FUT7, FUT9, FUT11, FUT12 and PIGV in HBV-HCC tissues.Although HCC and adjacent tissue samples in transcriptomic analysis can not represent the whole HCC progression, these data provide clues in understanding dysregulated glycosylation especially fucosylation in HBV-HCC.

N-glycan profiles of normal, hepatitis, cirrhosis and HCC serum samples
In our studies, N-glycans in HC, CHB, LC and HBV-HCC serum samples (Tab.S1) were profiled by MALDI-TOF/ TOF-MS to reveal abnormal N-glycosylation.Representative MS spectra of N-glycans with signal-to-noise ratios > 5 were displayed and annotated (Fig. 2; Table S5).A total of 36 distinct m/z N-glycan structures were identified, with 31, 32, 25 and 25 N-glycans present in HC, CHB, LC and HBV-HCC samples, respectively.There were 21 N-glycans found in all groups but with different intensities.
The expression pattern of identified N-glycans in HC, CHB, LC and HBV-HCC were exhibited in Fig. 3A.Hierarchical clustering revealed that LC/HBV-HCC were clearly separated from HC and CHB, however, LC/ HBV-HCC could not be separated from each other.Furthermore, quantitative comparison analysis revealed that 25, 24, and 22 N-glycan structures were differentially expressed in CHB, LC and HBV-HCC versus HC.Of these N-glycans, 11 N-glycans were concertedly  S5).N-glycans were classified into three types, including high mannose, complex and hybrid.Relative abundance of hybrid and complex N-glycans were increased in CHB, LC and HBV-HCC versus HC, while which of high mannose N-glycans were decreased (Fig. 3B).Consistent with elevated FUTs expression at mRNA levels, relative abundance of total fucosylation were up-regulated, of which mono-fucosylation levels were increased, while bi-fucosylation levels were decreased (Fig. 3C).Other terminal modification sialylation levels were increased, followed by a decrease in the progression of HBV-HCC (Fig. 3D).Significantly higher levels of bi-antennary structures were found in CHB, LC and HBV-HCC versus HC, while mono-antennary structures was progressively reduced (Fig. 3E).In combination of transcriptomic and glycomic analysis revealed that fucosylation levels were up-regulated in the progression of HBV-HCC.

Site-specific glycoproteomic profiling in HBV-HCC serum samples
To decode the biological function of specific N-glycosylation especially fucosylation in the progression of HBV-HCC, intact glycoproteomic analysis of HC, CHB, LC and HBV-HCC serum samples (Table S2) were performed.A total of 1114 glycopeptides were identified (Fig. 4A; Table S6), of which, 1019, 1011, 999 and 982 glycopeptides, including 864 in common were found in HC, CHB, LC and HBV-HCC serum samples, respectively.The identified glycopeptides represented 129 glycosites were modified with 102 glycan structures.These N-glycans contained 8 high mannose, 13 hybrid, 77 complex and 4 paucimannose subtypes (Fig. 4B).
Quantitative comparison analysis revealed that 116, 197 and 192 glycopeptides were differentially expressed in HC compared to CHB, LC and HCC, respectively, using the cutoff of fold change > 1.5 or < 0.67 and p Fig. 4 Quantitative glycoprotemic analysis of HC, CHB, LC and HBV-HCC serum samples.A Venn diagram of intact glycopeptides identified from HC, CHB, LC and HBV-HCC samples.B Distribution of glycan subtypes from intact glycopeptides identified from HC, CHB, LC and HBV-HCC samples.C Volcano plots of expression patterns of identified glycopeptides.Red dots: up-regulated glycopeptides.Green dots: down-regulated glycopeptides.The value q (-log10) is plotted against the log10 (FC: disease group vs. normal group).D Classification of differentially expressed intact glycopeptides based on their attached glycan structures.The numbers indicate the unique glycopeptides modified by the corresponding glycans value < 0.05 (Fig. 4C).These 288 differentially expressed glycopeptides (DEGPeps) from 73 glycoproteins were mainly decorated with complex type N-glycans, of which sialylated N-glycans accounted for the largest proportion, followed by fucosylated N-glycans and biantennary structures (Fig. 4D).
To understand the association between glycoprotein trajectories and the progression of HBV-HCC, hierarchical clustering for all DEGPeps was performed, with which four cluster (I-IV) were generated (Fig. 5A&B; Table S7).Glycopeptides in "cluster I" were continually increased in the progression of HBV-HCC, encompassing 27 proteins.These DEGPeps were significantly enriched in endopeptidase inhibitor activity, acute-phase response, blood microparticle and complement and coagulation cascades by functional enrichment analysis (Fig. 5C).Glycopeptides in "cluster II" were significantly decreased, followed by an increase (39 proteins), and mainly involved in the peptidase regulator activity, complement activation, blood microparticle and complement and coagulation cascades.Glycopeptides in "cluster III" were slightly decreased, followed by an increase (25 proteins), and enriched in regulation of humoral immune response, blood microparticle and complement and coagulation cascades.Glycopeptides in "cluster IV" (31 proteins) were decreased and primarily connected with peptidase regulator activity, acute-phase response, blood microparticle, complement and coagulation cascades.(Fig. S2).

Site-specific fucosylation on IgA1 and IgG2
We further mapped N-glycan structures on each glycosite of DEGPeps from IgA1 and IgG2 based on our glycoproteomics data.A total of 30 and 5 unique intact glycopeptides were identified from IgA1 and IgG2, which were comprised 3 glycosites ( 144 N # LT and 340 N # VS for IgA1, 176 N # ST for IgG2) and 31 glycans (Fig. 6A).Among these glycopeptides, fucosylation was accounted for 46% of all glycans on glycopeptides, and the majority of fucosylated intact glycopeptides were up-regulated in the progression of HBV-HCC.
Among these DEGPeps, 7 and 3 site-specific fucosylated glycopeptides from IgA1 and IgG2, showed a directionally concerted up-regulation in the HC-CHB-LC-HCC progression (Fig. 7A).To evaluate the diagnostic value of the aberrant fucosylated Igs in clinical practice, lectin-based ELISA assay with Concanavalin A (ConA), Lens Culinaris Agglutinin (LCA) and Aleuria Aurantia Lectin (AAL) was performed, which respectively recognize high mannose type N-glycans, α1,6-fucose, and α1,2/α1,3/α1,4/α1,6-fucose.The results revealed that total levels of IgG2 and IgA1 were not significantly changed, and different glycoform on Igs exhibited different expression patterns in the progression of HBV-HCC (Fig. 7B).AAL-reactive IgA1 and IgG2 were significantly elevated in HBV-HCC compared to HC, CHB and LC.LCA-reactive IgA1 was increased in HBV-HCC when In summary, combined results of glycoproteomic and ELISA analysis revealed that IgA1 and IgG2 are highly fucosylated and AAL-reactive fucosylated IgA1 and IgG2 were up-regulated in HBV-HCC, implying their potential diagnostic value.

Proteomic analysis of HBV-HCC serum samples
To comprehend the potential of the glycoproteins analysis and conclusions, proteomics of these samples have been performed, revealing 78, 163, and 186 differentially expressed proteins in HC compared to CHB, LC and HCC, respectively (Fig. 8A, Table S8).Among these differentially expressed proteins, 21 proteins, including AFP and diverse Igs, were up-regulated (p < 0.05) in patients with liver disease (CHB, LC, or HBV-HCC) compared to HC (Fig. 8B), that were mainly enriched in the cellular components of immunoglobulin complex, blood microparticle and cell periphery, the biological process of adaptive immune response, and molecular function of antigen binding (Fig. 8C).Notably, IgA1 did not show significant differences, while IgG2 was significantly up-regulated in patients with liver disease compared to HC (Fig. 8B).Peptides corresponding to the differentially expressed glycopeptides of Igs were investigated.The non-glycosylated peptides from IgA1 (amino acids 332-353; termed as IgA1[332-353]) did not show significant differences in the progression of HBV-HCC, while IgA1[127-153] and IgG2[172-180] were only detected in HBV-HCC (Fig. 8D), suggesting that fucosylated peptides from IgA1 and IgG2, especially IgA1[332-353], were specially up-regulated in the progression of HBV-HCC.
Furthermore, we correlated the abundance of glycopeptides with total corresponding peptides levels to determine the glycosylation site occupancy (Table S9).We found that the average site occupancy did not significantly changed (Fig. 8E).The glycosylation site occupancy of IgA1[127-153] and IgG2[172-180] exhibited no significant changes in the progression of HBV-HCC, and which of IgA1[332-353] was decreased in CHB compared to HC (Fig. 8F).Specifically, N-glycans on IgG2[172-180] were mainly fucosylated, and fucosylation site occupancy of IgA1[332-353] was elevated in LC and HCC compared to HC (Fig. 8G).
Collectively, When the IgA1 remains unchanged at protein levels, the fucosylation site occupancy of IgA1[332-353] increases, leading to a rise in IgA1[332-352]-N5H5F1S2 or -N6H3F1S2 and consequently resulting in elevated levels of AAL-reactive IgA1 in HBV-HCC.When fucosylation site occupancy of IgG2[168-180] remains unchanged, the IgG2 exhibited a upregulation at protein levels, contributing to a rise in IgG2[168-180]-N4H5F2 and consequently leading to a elevated level of LCA-and AAL-reactive IgG2 in HBV-HCC.

Discussion
An alteration in glycosylation have long been observed with the progression of HBV-HCC [36,37].Our study comprehensively characterizes the transcriptomics, glycomics and glycoproteomics landscapes of HC, CHB, LC and HBV-HCC, which allows us to interrogate underlying mechanisms in HBV-HCC progression.Our transcriptomic analysis revealed that several FUTs responsible for the N-glycan fucosylation were dysregulated in HBV-HCC (Fig. 1F).FUT1 catalyzes the addition of fucose to a terminal galactose in an α1,2-linkage, while FUT4, 6, 7, 9 catalyze the formation of α1,3-fucosylation on terminal GlcNAc, and FUT8 catalyze the core-α1,6-fucosylation on the innermost GlcNAc of core pentasaccharide.Consistently, our glycomic analysis revealed that most of concertedly up-regulated N-glycans in the progression of HBV-HCC were annotated to be fucosylated (Fig. 3C), in line with the up-regulation of FUT1, 4, 8. Recent studies also observed an elevated serum core-fucosylation by HPLC [38], and an elevated saliva fucosylation by saliva microarrays with Lotus Tetragonolobus Lectin [39] in the progression of human HBV-HCC.Moreover, a serumassociated fucosylated glycoprotein (< 10 kD) fingerprint was established to assist the diagnosis of HBV-HCC by using MALDI-TOF-MS, which could distinguish HBV-HCC from healthy subjects, patients with HBV and HBV-associated cirrhosis [40].
Furthermore, we found that most of concertedly upregulated N-glycans were decorated with mono-fucosylated bi-/tri-antennary.Specifically, the up-regulation of the core-fucosylated monogalactose biantennary glycan (N4H4F1) is in agreement with the previously reported study [34].In situ glycan imaging also revealed that fucosylation mostly on tetra-antennary and to a lesser extent on bi-antennary and tri-antennary glycans were elevated in HCC [24] in line with the elevated fucosylated tri-antennary N-glycans (N5H3F1, N5H4F1, N5H5F1) in our glycomic analysis.Xue-En Liu et al. found that a branch α1,3-fucosylated tri-antennary N-glycan (NA3Fb) was elevated in patients with HBV-HCC compared to who with HBV-fibrosis or cirrhosis or healthy subjects by using a DNA sequencer [41], furthermore, the log ratio of NA3Fb/NG1A2F was elevated in HBV-HCC, which was promising as N-glycan markers [42].While, we found that levels of N5H6F1 N-glycan (the same component as NA3Fb) were reduced in HBV-HCC.This discrepancy might arise from inefficient distinction between N-glycan isoforms of MALDI-TOF-MS.
Advances in glycomics, genomics and proteomics platforms over the last decade have discovered numerous novel biomarkers and have improved the diagnosis of HBV-HCC.In recent years, the glycoproteome mapping provides innovative insights into the both peptides and glycosylation status in diseases and contributes to biomarker discovery.As the predominant constituent in immune molecule, Ig glycosylation especially fucosylation variations were found to be closely associated with the development of HBV-HCC using glycoproteomics [43].Core-fucosylated serum IgG was significantly increased in HBV-HCC compared to HBV-related cirrhosis, HBV carriers and healthy subjects, and have general diagnostic performance than AFP in the training set and validation cohorts [44].Similar research revealed that TPLTAN 205 ITK (H5N5S1F1) and (H5N4S2F1) of IgA2 were significantly elevated in serum from patients with HBV infection and even higher in HBV cirrhosis in comparison with healthy donor [45].Consistently, in the present study, 30 N-glycan structures on 2 glycosites of IgA1 and 5 N-glycans on 1 glycosite of IgG2 were identified.Specifically, differentially expressed IgA1 with fucosylated glycan structures (IgA1-144-N4H4F2/N5H4F2/ N5H5F1S1/N5H5F2/N5H5F3 and IgA1-340-N5H5F1S2/ N5H5F3/N6H3F1S2) and IgG2 with fucosylated glycan structures (IgG2-176-N4H3F1/N4H4F1/N5H3F1) were elevated in the progression of HBV-HCC determined by glycoproteomics.
Since each fucosylated glycoform can be recognized by a distinct lectin, a lectin-based ELISA was used to quantify the fucosylated Igs, which is more appropriate for the clinical practice.The present study revealed that the elevated AAL-reactive IgA1 and IgG2 in HBV-HCC might distinguish HBV-HCC from HC, CHB and LC.Similarly, the reduced LCA-reactive IgA1 in HBV-HCC might distinguish HBV-HCC from other groups, while the elevated LCA-reactive IgG2 in CHB, LC and HBV-HCC might distinguish liver diseases from HC, and even distinguish LC from other groups.These results indicated that LCA-and AAL-reactive Igs showed a diagnostic potential in distinguishing HBV-HCC from HC, CHB and LC.
Therefore, we speculate that changes in serum IgG and IgA glycosylation may closely correlate to the progression of HCC, and act as complementary techniques to improve diagnosis.

Fig. 2
Fig. 2 MALDI-TOF/TOF-MS spectra of N-glycans in HC, CHB, LC and HBV-HCC serum samples.Peaks of MALDI-TOF/TOF-MS spectra (signal-to-noise ratio > 5) were selected for relative intensity analysis in HC (A), CHB (B), LC (C) and HBV-HCC (D) samples.Detailed structures were annotated with GlycoWorkbench software.Proposed structures are indicated by m/z value

Fig. 3 N
Fig. 3 N-glycan levels in HC, CHB, LC and HBV-HCC serum samples.A Expression pattern and dysregulation of N-glycans identified in HC, CHB, LC and HBV-HCC.B Relative abundances of high mannose, complex and hybrid N-glycans.The relative abundance is calculated by adding the relative abundances of a given type of N-glycan.C Relative abundances of bi-, mono-and afucosylated N-glycans.D Relative abundances of bi-, mono-and asialylated N-glycans.E Relative abundances of N-glycans with mono-, bi-and tri/tetra-antennary structures

Fig. 5
Fig. 5 Hierarchical clustering analysis of differentially expressed glycopeptides identified in HC, CHB, LC and HBV-HCC.A Mfuzz clustering of differentially expressed glycopeptides.B Expression pattern of glycopeptides from cluster I, II, III and IV.C Functional enrichment analysis of differentially expressed glycopeptides from cluster I. D Heatmap of fucosylated N-glycans on intact glycopeptides from cluster I. PSMs of the intact glycopeptides, comprising of different glycans (bottom) and their glycosite locations in different glycoproteins (right) are exhibited in the heat map

Fig. 7
Fig. 7 Differentially expressed intact glycopeptides of IGHA1 and IGHG2.A Box plots of 10 site-specific fucosylated glycopeptides from IgA1 and IgG2 showed a directionally concerted up-regulation in the HC-CHB-LC-HCC progression.B Relative expression of IgA1/ IgG2 and ConA-/ LCA-/ AAL-reactive IgA1/ IgG2 in the HC, CHB, LC and HBV-HCC serum determined by ELISA